New experimental techniques for fracture testing of highly deformable materials by E. Dall’Asta, V. Ghizzardi, R. Brighenti, E. Romeo, R. Roncella, A. Spagnoli

“…SGM approach is compared with the previously in-house developed implementation based on a local Least Squares Matching (LSM) approach. …”
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Health risks associated with infertility and non-obstructive azoospermia by Eric Huyghe, Peter Ka-Fung Chiu

“…This review aims to highlight the potential health challenges faced by men with this condition compared to fertile counterparts. Through a comprehensive bibliographic search on PubMed, using the following algorithm: (“infertility, male” [MeSH Terms] OR “azoospermia” [MeSH Terms]) AND (“mortality” [MeSH Terms] OR “neoplasms” [MeSH Terms] OR “chronic disease” [MeSH Terms] OR “diabetes mellitus” [MeSH Terms] OR “heart diseases” [MeSH Terms]), we analyzed existing literature to explore the associations between infertility, specifically azoospermia, and adverse health outcomes. …”
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Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

“…Hyperparameter tuning is conducted using the Limited-memory Broyden–Fletcher–Goldfarb–Shanno with Box constraints (L-BFGS-B) algorithm, which demonstrates the superior computational efficiency compared to traditional approaches such as grid and random search. …”
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Numerical Simulation and Optimization of Wind Effects of Porous Parapets on Low-Rise Buildings with Flat Roofs by Ye Qiu, Bingbing San, Youyi Zhao

“…This paper presents a procedure to optimize the porosity of parapets to improve the aerodynamic behavior of low-rise buildings with flat roofs, by coupling an optimization algorithm and computational fluid dynamics (CFD) simulations. …”
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Network Dismantling on Signed Network by Evolutionary Deep Reinforcement Learning by Yuxuan Ou, Fujing Xiong, Hairong Zhang, Huijia Li

“…To address these questions, in this paper, we design a new objective function and further propose an effective algorithm named as DSEDR, which aims to search for the best dismantling strategy based on evolutionary deep reinforcement learning. …”
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Improved Set-point Tracking Control of an Unmanned Aerodynamic MIMO System Using Hybrid Neural Networks by Oduetse Matsebe, David Mohammed Ezekiel, Ravi Samikannu

“…ANN as a Hybrid intelligent control strategy of ANN in combination with Pattern Search and Genetic Algorithm, is then utilized to optimize the parameters of the neural networks. …”
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SOH Prediction of nickel-cadmium battery based on the charging time under constant voltage rise by SUN Ning, WANG Shenghui, YU Tianjian, DAI Yi

“…This method determined the optimal constant voltage rising range (i.e. the voltage difference between the start and end of charging) through a comprehensive correlation analysis of charging time under constant voltage rise and battery SOH based on moving voltage window, and then extracted the optimal charging time under constant voltage rise from the voltage range as the input for the long short-term memory (LSTM) model. The sparrow search algorithm (SSA) was used to optimize the LSTM parameters, establishing a battery SOH prediction model, and realizing the online prediction of battery SOH. …”
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Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 by Leixin Zhang, Feng Zhao, Yunjia Wang, Jordi J. Mallorqui, Teng Wang, Yuxuan Zhang, Zhongbo Hu, Sen Du, José Fernández

“…While achieving a nearly equivalent number of monitoring pixels as the optimal exhaustive search polarimetric optimization (ESPO) algorithm, ADCMD-PolMTI operates 235 and 13 times faster for PSs and DSs, respectively. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…For multi-step predictions, the total experiment time, which includes the hyperparameter optimization phase, was also observed to be lower for the ESN-EICM compared to the standard ESN. This efficiency gain during optimization is attributed to the model's intrinsic stability, which reduces the number of divergent trials encountered by the search algorithm.DiscussionThe results indicate that the ESN-EICM framework is a viable method for the prediction of the tested chaotic time series. …”
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Hummingbird-Inspired Modified Particle Swarm Optimization for Efficient Task Scheduling in Cloud Computing by Longyang Du, Qingxuan Wang

“…Five hummingbirdinspired concepts are integrated into PSO: incremental position updates to enhance convergence accuracy, stepwise position changes to avoid local optima, energy-conserving movements reducing computational overhead, decentralized exploration to maintain diversity, and multidirectional searches enhancing solution coverage. Comparative experiments conducted on synthetic and real-world datasets (HPC2N) with diverse task loads demonstrate measurable performance improvements, including up to 18% better resource utilization, up to a 35% decrease in imbalance degree, and up to a 20% improvement in execution cost compared to recent algorithms. …”
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Network Partitioning Domain Knowledge Multiobjective Application Mapping for Large-Scale Network-on-Chip by Yin Zhen Tei, Yuan Wen Hau, N. Shaikh-Husin, M. N. Marsono

“…NP reduces the large-scale application mapping complexity and provides GA with a potential mapping search space. The proposed genetic operator is compared with state-of-the-art genetic operators in terms of solution quality. …”
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An Efficient K-Best MIMO Detector for Large Modulation Constellations by Yu-Xin Liu, Shih-Jie Jihang, Yeong-Luh Ueng

“…The <inline-formula> <tex-math notation="LaTeX">$K \sqrt {M}$ </tex-math></inline-formula> candidates are arranged into a multiple-layer table using the proposed path metric discretization. A bisection-based search algorithm is used to obtain the locations of the <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> surviving candidates. …”
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Evolution and Knowledge Structure of Wearable Technologies for Vulnerable Road User Safety: A CiteSpace-Based Bibliometric Analysis (2000–2025) by Gang Ren, Zhihuang Huang, Tianyang Huang, Gang Wang, Jee Hang Lee

“…Guided by PRISMA procedures and a PICo-based search strategy, 58 records were extracted and analyzed in CiteSpace, yielding visualizations of collaboration networks, publication trajectories, and intellectual structures. …”
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SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions by De-yu Tang, Yi-jun Mao, Jie Zhao, Jin Yang, Shi-yin Li, Fu-xiang Ren, Junxi Zheng

“…The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). Bayesian optimization was used for global tuning of network structural parameters, while ASFSSA was applied to fine-tune the initial weights and thresholds, improving convergence efficiency and predictive accuracy. …”
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Examining Nasdaq Market Data and Presenting an Optimized Model by Extreme Gradient Boosting Regression and Artificial Bee Colony by Ali Ahmadpour

“…These outcomes underscore the effectiveness of combining machine learning with nature-inspired optimization algorithms to produce more accurate stock price forecasts. …”
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Doppler Shift Estimation Method for Frequency Diverse Array Radar Based on Graph Signal Processing by Ningbo Xie, Haijun Wang, Kefei Liao, Shan Ouyang, Hanbo Chen, Qinlin Li

“…Furthermore, the proposed method exhibits superior performance compared to the MUSIC algorithm, offering enhanced resolution and estimation accuracy. …”
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LogProb: Online Parsing Evolving Logs With Complex Parameters by Yan Li, Ziying Wang, Jiaming Mao, Zhimin Gu, Haitao Jiang

“…The extraction process includes two stages: identifying candidate templates with predicted static tokens, and using a fast matching algorithm to determine the final template. Experiments on 16 benchmark datasets show that LogProb outperforms state-of-the-art methods in accuracy while maintaining comparable efficiency.…”
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Risk-Aware Vessel Scheduling and Routing Optimization with CVaR and LSTM-MSNet Prediction by Zhichao Cao, Zhiwei Zhu, Weike Lu, Silin Zhang

“…Two hybrid heuristics, one adaptive large-neighborhood search algorithm, and the Gurobi solver are devised and compared based on the efficiency and accuracy of solving the model. …”
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Multiobjective Approach to the Transit Network Design Problem with Variable Demand considering Transit Equity by Su Jin Park, Seungmo Kang, Young-Ji Byon, Seung-Young Kho

“…In particular, the multiobjective Nondominated Sorting Genetic Algorithm-II and the neighborhood local search method are employed in a logit-based mode-choice model in order to incorporate the variable transit demand arising from the private vehicle traffic volume. …”
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